Multiple chromosomal inversions contribute to adaptive divergence of a dune sunflower ecotype
Bibliographic record
Abstract
Both models and case studies suggest that chromosomal inversions can facilitate adaptation and speciation in the presence of gene flow by suppressing recombination between locally adapted alleles. Until recently, however, it has been laborious and time-consuming to identify and genotype inversions in natural populations. Here we apply RAD sequencing data and newly developed population genomic approaches to identify putative inversions that differentiate a sand dune ecotype of the prairie sunflower (Helianthus petiolaris) from populations found on the adjacent sand sheet. We detected seven large genomic regions that exhibit a different population structure than the rest of the genome and that vary in frequency between dune and nondune populations. These regions also show high linkage disequilibrium and high heterozygosity between, but not within, arrangements, consistent with the behaviour of large inversions, an inference subsequently validated in part by comparative genetic mapping. Genome-environment association analyses show that key environmental variables, including vegetation cover and soil nitrogen, are significantly associated with inversions. The inversions colocate with previously described "islands of differentiation," and appear to play an important role in adaptive divergence and incipient speciation within H. petiolaris.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".